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Reliability assessment of infinite slope stability using the jointly distributed random variables method

SCIENTIA IRANICA 2012年第3期19卷 423-429页

作者： Johari, A. Javadi, A. A. Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran Univ Exeter Coll Engn Math & Phys Sci Computat Geomech Grp Exeter EX4 4QF Devon England

Slope stability analysis is a branch of geotechnical engineering that is highly amenable to probabilistic treatment. Probabilistic analysis of slope stability has received considerable attention in the literature, and has been used as an effective tool to evaluate uncertainty that is so prevalent in variables. In this research, the jointly distributed random variables method is used for probabilistic analysis and reliability assessment of the stability of infinite slopes without seepage. The selected stochastic parameters are internal friction angle, cohesion and unit weight, which are modeled using a truncated normal probability distribution function. The geometric parameters, such as height of slope and angle of slope relative to horizontal, are regarded as constant parameters. The results are compared with the Monte Carlo, Point Estimated, and First Order Second Moment methods. Comparison of the results indicates the superior performance of the proposed approach for assessment of reliability. (c) 2012 Sharif University of Technology. Production and hosting by Elsevier B.V. All rights reserved.

关键词： Reliability jointly distributed random variables method Monte Carlo method Point estimated method First order second moment method Infinite slope stability

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Modelling of probability liquefaction based on standard penetration tests using the jointly distributed random variables method

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ENGINEERING GEOLOGY 2013年 158卷 1-14页

作者： Johari, A. Khodaparast, A. R. Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran

Soil liquefaction during an earthquake can be a major cause of damage to structures. The inherent variability of the soil parameters which affect liquefaction potential dictates that the problem is of a probabilistic nature rather than being deterministic. Probabilistic assessment of liquefaction potential has received considerable attention in the past few years. In this research, the jointly distributed random variables (JDRV) method is used as an analytical method to develop a model for probability of liquefaction potential based on standard penetration tests. The selected stochastic parameters are corrected SPT blow count and stress reduction factor, which are modeled using a truncated normal probability density function and the peak horizontal earthquake acceleration ratio and earthquake magnitude, which are considered to have a truncated exponential probability density function. The depth of water table and fines content are regarded as constant parameters. The results of JDRV method are verified with those of the Monte Carlo simulation. It is shown that the moment magnitude is the most effective parameter in soil liquefaction potential. Comparison of the model results indicates reasonable performance of the proposed approach in assessment of probability of liquefaction and empirical data. (c) 2013 Elsevier B.V. All rights reserved.

关键词： Probability jointly distributed random variables method Monte Carlo simulation Liquefaction Standard penetration tests

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Coordination of combined heat and power-thermal-wind-photovoltaic units in economic load dispatch using chance-constrained and jointly distributed random variables methods

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ENERGY 2015年第C期79卷 50-67页

作者： Azizipanah-Abarghooee, Rasoul Niknam, Taher Bina, Mohammad Amin Zare, Mohsen Shiraz Univ Technol Dept Elect & Elect Engn Shiraz 71555313 Iran Iran Fars Shiraz Fars Elect Power Distributed Co Shiraz Iran

CHP (Combined heat and power) generation or cogeneration has been considered worldwide as the major alternative to traditional systems in terms of significant energy saving and environmental conservation. Furthermore, the wind power generators and photovoltaic units have vastly speared over the power systems due to their free inputs. However, there are many challenges for power system operators because of uncertain characteristics of renewable units and load demands. Therefore, a new multi-objective stochastic framework based on chance constrained programming is developed to handle combined heat and power economic load dispatch considering the stochastic characteristics of wind and photovoltaic power outputs, customer's electrical and heat load demands. The proposed technique makes use of a jointly distributed random variables method to calculate chance of meeting the electrical and heat load requirement using the target decision variables while maintaining the electrical energy cost below a scheduled value. The framework benefits from a new method named hybrid modified cuckoo search algorithm and differential evolution to extract the Pareto optimal surface for minimum cost and maximum probability of meeting the target cost and applies them as the objective functions. Applying to 6 and 40 unit test systems, the ability of the suggested framework is confirmed. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Combined heat and power economic dispatch Chance constrained programming Cuckoo search algorithm jointly distributed random variables method Stochastic multi-objective optimization Photovoltaic and wind power

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An analytical probabilistic analysis of slopes based on limit equilibrium methods

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BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT 2019年第6期78卷 4333-4347页

作者： Johari, A. Mousavi, S. Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran Shahid Beheshti Univ Dept Civil Water & Environm Engn Tehran Iran

Probabilistic analysis of slopes has been used as an effective tool to evaluate uncertainty that is so prevalent in variables. In this paper, the jointly distributed random variables (JDRV) method is used as an analytical method to compare the reliability of four widely used limit equilibrium methods for slope stability analysis. These methods include the simplified Bishop, simplified Janbu, Morgenstern-Price, and Spencer's methods. The selected stochastic parameters are angle of shearing resistance (phi), cohesion intercept (c), and unit weight (gamma) of soil, which are modeled using a truncated normal probability distribution function. Geometric parameters such as height and angle of the slope relative to the horizontal are regarded as constant parameters. For reliability assessment, the reliability indices of the limit equilibrium methods for the critical surface with minimum factor of safety are determined by the particle swarm optimization (PSO) technique. It is shown that, among the assessed methods, the Janbu and Bishop methods are those with upper and lower probabilities of failure, respectively, in two conditions with and without considering cross correlation between c and phi.

关键词： Probabilistic analysis jointly distributed random variables method Slope stability Limit equilibrium method

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Analytical System Reliability Analysis of a Geotextile-Reinforced Retaining Wall

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INTERNATIONAL JOURNAL OF GEOMECHANICS 2024年第10期24卷

作者： Johari, A. Elyasi, H. Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran

A geotextile-reinforced retaining wall is a geotechnical structure with many design parameters. Hence, the uncertainty of the input parameters considerably affects the design of these structures. On the other hand, when the number of uncertain parameters increases, the time of this analysis increases drastically. Accordingly, the current study used an analytical method, namely, jointly distributed random variables (JDRV) method, that requires less running time than the simulation methods for stochastic analysis. For this purpose, stochastic analysis of the geotextile-reinforced retaining wall was carried out based on the limit equilibrium method (LEM), with soil parameters considered as uncertain variables. To verify the results, the probability density functions (PDFs) of the wall safety factors were compared with the Monte Carlo simulation (MCS). Next, to assess the effect of the external and internal stability modes on system reliability, the system reliability index was determined using the sequential compounding method (SCM). The results of the system reliability analysis revealed that, among the reliability indices of the components, the minimum values are attributed to the bearing capacity. The correlation between the rupture and pullout safety factors exhibited the maximum correlation, indicating that they are more dependent components than others. Based on the stochastic sensitivity analysis, the internal friction angle emerged as the most influential in the external and internal safety factors.

关键词： Analytical system reliability analysis Geotextile-reinforced retaining wall jointly distributed random variables method Monte Carlo simulation Limit equilibrium method

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Analytical stochastic analysis of seismic stability of infinite slope

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SOIL DYNAMICS AND EARTHQUAKE ENGINEERING 2015年第PartA期79卷 17-21页

作者： Johari, A. Khodaparast, A. R. Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran

The sliding of natural slopes is usually governed by combination of soil parameters and earthquake characteristics. The inherent variability of these parameters which affect seismic slope stability dictates that the problem is of a probabilistic nature rather than being deterministic. Stochastic analysis of slope seismic stability has received attention in the literature and has been used as an effective tool to evaluate uncertainty so prevalent in the variables. In this research, the jointly distributed random variables method is used as an analytical method for stochastic analysis and reliability assessment of seismic stability of infinite slopes without seepage. The selected stochastic parameters are internal friction angle, cohesion and unit weight of soil, which are modeled using a truncated normal probability density function and the horizontal seismic coefficient which is considered to have a truncated exponential probability density function. The geometric parameters such as height and angle of the slope relative to a horizontal are regarded as constant parameters. The results are compared with the Monte Carlo simulation. Comparison of the results indicates superior performance of the proposed approach for assessment of reliability. (c) 2015 Elsevier Ltd. All rights reserved.

关键词： Stochastic analysis jointly distributed random variables method Infinite slope seismic stability Monte Carlo simulation

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An Analytical Approach to Probabilistic Modeling of Liquefaction Based on Shear Wave Velocity

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IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING 2019年第1期43卷 263-275页

作者： Johari, A. Khodaparast, A. R. Javadi, A. A. Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran Univ Exeter Dept Engn Computat Geomech Grp Exeter EX4 4QF Devon England

Evaluation of liquefaction potential of soils is an important step in many geotechnical investigations in regions susceptible to earthquake. For this purpose, the use of site shear wave velocity (V-s) provides a promising approach. The safety factors in the deterministic analysis of liquefaction potential are often difficult to interpret because of uncertainties in the soil and earthquake parameters. To deal with the uncertainties, probabilistic approaches have been employed. In this research, the jointly distributed random variables (JDRV) method is used as an analytical method for probabilistic assessment of liquefaction potential based on measurement of site shear wave velocity. The selected stochastic parameters are stress-corrected shear wave velocity and stress reduction factor, which are modeled using a truncated normal probability density function and the peak horizontal earthquake acceleration ratio and earthquake magnitude, which are considered to have a truncated exponential probability density function. Comparison of the results with those of Monte Carlo simulation indicates very good performance of the proposed method in assessment of reliability. Comparison of the results of the proposed model and a standard penetration test (SPT)-based model developed using JDRV shows that shear wave velocity (V-s)-based model provides a more conservative prediction of liquefaction potential than the SPT-based model.

关键词： Reliability jointly distributed random variables method Monte Carlo simulation Liquefaction Shear wave velocity

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Probabilistic approach for quantification of uncertainties in shear wave velocities and hazard calculation of liquefiable soil

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INNOVATIVE INFRASTRUCTURE SOLUTIONS 2024年第5期9卷 1-21页

作者： Behzadpour, Maryam Bagheripour, Mohammad Hossein Bagheri, Fatemeh Shahid Bahonar Univ Kerman Civil Engn Dept Kerman Iran

Uncertainties governing soil parameters indicate that liquefaction in loose, saturated, sandy soils is related to probabilistic nature of these parameters. Hence, statistical approaches and especially the reliability analysis are often used as an alternative to the deterministic methods and as a powerful solution to the problem of liquefaction hazard analysis. In this paper, the method of jointly distributed random variable is used to evaluate the probability of soil liquefaction potential. The corrected shear wave velocity (Vs), peak horizontal earthquake acceleration ratio (alpha), and earthquake magnitude (Mw) are considered as stochastic parameters which are modeled using a normal probability density function. In contrast to the most of the past studies, the seismic parameters (Mw, alpha) are here assumed to follow the normal distribution leading to results which are more logically comparable with other concepts, especially those which are based FORM & FOSM & PEM. Further, a formula proposed by Idriss 1999 for variation of parameter rd is used in the current study which is based on the earthquake magnitude Mw and depth. This further enables the authors to reduce the number of selected parameters to three. In order to study the performance of the proposed method, the liquefaction potential of Taiwan's Yuanlin region, affected by Chi-Chi earthquake, has been studied. The results show the effectiveness and speed of calculation of the proposed method.

关键词： Liquefaction Reliability method jointly distributed random variables method Monte Carlo simulation Shear wave velocity

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Analytical reliability assessment of liquefaction potential based on cone penetration test results

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SCIENTIA IRANICA 2014年第5期21卷 1549-1565页

作者： Johari, A. Khodaparast, A. R. Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran

Determination of site liquefaction potential and subsequent deterrent action can prevent significant damage to structures. In this way, a probabilistic liquefaction assessment can develop potential flexibility and risk management decisions. Based on the advantage of probabilistic assessment, considerable research has been carried out in the past few years on liquefaction potential. In this research, the jointly distributed random variables method is used as an analytical method for probabilistic analysis and reliability assessment of liquefaction potential based on cone penetration test results. The selected stochastic parameters are corrected CPT tip resistance and the stress reduction factor, which are modeled using a truncated normal probability density function and peak horizontal earthquake acceleration ratio and magnitude, which are considered to have a truncated exponential probability density function. The depth of the water table and fines content are regarded as constant parameters. The results are compared with those of the Monte Carlo simulation. Comparison of the results and parametric analysis indicates the very good performance of the proposed approach in the assessment of reliability. A sensitivity analysis shows that the moment magnitude is the most effective parameter in soil liquefaction potential. (C) 2014 Sharif University of Technology. All rights reserved.

关键词： Reliability jointly distributed random variables method Monte Carlo simulation Liquefaction Standard penetration test

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A seismic slope stability probabilistic model based on Bishop's method using analytical approach

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SCIENTIA IRANICA 2015年第3期22卷 728-741页

作者： Johari, A. Mousavi, S. Nejad, A. Hooshmand Shiraz Univ Technol Dept Civil & Environm Engn Shiraz Iran

Probabilistic seismic slope stability analysis provides a tool for considering uncertainty of the soil parameters and earthquake characteristics. In this paper, the jointly distributed random variables (JDRV) method is used as an analytical method to develop a probabilistic model of seismic slope stability based on Bishop's method. The selected stochastic parameters are internal friction angle, cohesion and unit weight of soil, which are modeled using a truncated normal probability density function (pdf) and the horizontal seismic coefficient which is considered to have a truncated exponential probability density function. Comparison of the probability density functions of slope safety factor with the Monte Carlo simulation (MCs) indicates superior performance of the proposed approach. However, the required time to reach the same probability of failure is greater for the MCs than the JDRV method. It is shown that internal friction angle is the most influential parameter in the slope stability analysis of finite slopes. To assess the effect of seismic loading, the slope stability reliability analysis is made based on total stresses without seismic loading and with seismic loading. As a result, two probabilistic models are proposed. (C) 2015 Sharif University of Technology. All rights reserved.

关键词： Reliability jointly distributed random variables method Monte Carlo simulation Seismic slope stability Limit equilibrium method

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